Search pathology Games and search Bioinformatics Tourism
Machine learning Genre classification Other

Search pathology

Search pathology is a phenomenon best known from minimax search, where under seemingly reasonable conditions, the deeper one searches, the worse he plays - the opposite of what happens in practice. Similar behavior was observed in real-time single-agent heuristic search. Search pathology was the subject of my Ph. D. thesis under the supervision of Ivan Bratko and Matjaž Gams. My research on the pathology in single-agent search was done in collaboration with Vadim Bulitko.

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Bioinformatics

I started working in this area as a postdoc at the Institute for Biostatistics and Informatics in Medicine and Ageing Research. I developed a machine-learning method for epitope prediction based on peptide array data, which is relevant to vaccine design and diagnostics. I am also involved in the research on pluripotency.

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Tourism

We have developed an intelligent electronic tourist guide as a web and mobile application. The guide prepares a personalized itinerary for each user and then guides him on his trip. The personalization relies on knowledge-based recommendations and collaborative filtering.

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Games and search

Computer game playing was the subject of my B. Sc. thesis, for which I wrote a program for playing tarok called Silicon Tarokist. The program was substantially improved afterwards. I later also collaborated with Domen Marinčič, who worked on a Bayesian decision model for bidding in tarok. I have also done some research on real-time single-agent heuristic search, where I was investigating methods to determine the optimal lookahead depth. This research is an offshoot of the research on search pathology and was also done in collaboration with Vadim Bulitko.

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Machine learning

While I use machine learning in most of my research, I do not often research machine learning itself. My main interest in this area is building classifiers that are both comprehensible and accurate.

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Genre classification

The ability to classify web pages into genres can be a helpful addition to a search engine. We developed machine learning methods for genre classification in Alvis EU FP6 project, but the development continues after the end of the project. I collaborate on this with Vedrana Vidulin.

The web genre dataset used in our research

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Other

Occasionally I also dabble in other areas.

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